Fertilizer markets and their interplay with commodity and food prices 

Hervé Ott  2012  

Report EUR 25392 EN 

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European Commission 

Joint Research Centre 

Institute for Prospective Technological Studies 

 

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JRC 73043 

 

EUR 25392 EN 

 

ISBN 978‐92‐79‐25526‐7 (pdf) 

 

ISSN 1831‐9424 (online) 

 

doi:10.2791/82136 

 

Luxembourg: Publications Office of the European Union, 2012 

 

© European Union, 2012 

 

Reproduction is authorised provided the source is acknowledged. 

 

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   Acknowledgements  

The author warmly thanks Anna Atkinson, Pavel Ciaian, Jacques Delincé, Robert M'Barek, and Silvia Saravia‐Matus for their contribution regarding the editing of the text and the structuring of the technical report.         The views expressed are purely those of the author and may not in any circumstances be regarded as stating an official position of the European Commission.

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TABLE OF CONTENTS

Acknowledgements .................................................................................................... 3

TABLE OF CONTENTS ............................................................................................. 4

1 Introduction............................................................................................................. 5

2 Literature review and hypothesis...................................................................... 6

3 Data............................................................................................................................ 8

4 Stylized facts........................................................................................................... 8 4.1 FERTILIZER PRICES.............................................................................................................................. 8

4.2 POTENTIAL FACTORS EXPLAINING THE FERTILIZER PRICE ............................................................... 10

5 The role of speculations in fertilizer price formation ................................ 17 5.1 IDENTIFICATION OF SPECULATIONS (BUBBLES)................................................................................ 19

5.2 RELATIONSHIP BETWEEN DERIVATIVE AND PHYSICAL FERTILIZERS MARKET .................................. 21

5.3 INTERACTION BETWEEN FUTURE AND PHYSICAL MARKET................................................................ 22

5.4 MEASURING SPECULATIVE ACTIVITY IN THE DERIVATIVE MARKET ................................................... 23

6 Price interaction between fertilizers, food and energy ............................. 24 6.1 VAR ANALYSIS .................................................................................................................................. 25

7 Fertilizers price volatility ................................................................................... 27

8 Conclusion ............................................................................................................ 29

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1 Introduction

Fertilizers are among the major production factors to increase agricultural output.

They accounted for approximately 60% of the registered yield increase in the last

50 years (Steward et al., 2005). Consequently, if the agricultural sector is to

produce sufficient feed and food for the future requirements of an additional 2

billion people by 2050, efficient access to fertilizers is a relevant issue,

particularly in the least developed areas. In Africa, closing the gap between

actual and potential agricultural yields, which could mitigate food insecurity,

depends heavily on improved access to and use of fertilizers (Saravia-Matus et

al., 2012; Malingreau et al., 2012).

Food commodity prices reached unprecedented levels in 2007-2008 and, at the

same time, the sudden rise of their price level and volatility added to insecurity

and fears in national and international markets. According to the FAO (2009), the

reduced supply response of smallholders (largely in low income areas) was partly

explained by the simultaneous increase in the cost of inputs. Compared to the

last 20 year period, today's prices for agricultural commodities like wheat and

maize are still high and continue to experience high volatility. The factors in play

which may explain the food price swings have been reviewed in Baffes and

Haniotis (2010): low agricultural investment in the past, weak dollar, fiscal

expansion, lax monetary policy, reduced global stocks and index fund investment

in commodities. Regarding the activity of the index fund, De Schutter (2010) and

Roblel et al. (2009) argue that since the US Commodity Futures Modernization

Act in 2000, 'speculative capital' entered the commodity market on a massive

scale. The entry of index funds caused the number of futures and options "traded

globally on commodity exchanges to increase by more than 5 times between

2002 and 2008" (De Schutter, 2010), which in turn destabilized the physical food

market affecting food security at local, national and world levels.

This study is structured to address three main objectives related to the fertilizer

market and its interplay with food and energy markets. The first objective is to

investigate whether speculative activity may have affected fertilizer prices. The

second objective is to analyse how the food commodity prices, the fertilizer

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prices, and the energy prices interact. The third objective is to analyse the

volatility of fertilizer prices. Regularly, politicians and market analysts blame

speculation and the derivatives market for destabilizing the physical markets

(Masters, 2008; Robles et al., 2009); whereas experts in fertilizer markets point

to the fundamental structural factors in play (Huang, 2009). This study will shed

light on this controversy by reviewing academic and policy documents on the

subject and analysing relevant fertilizer, fuel and food commodity data. The

objectives mentioned above will be pursued in three steps: firstly by reporting

selected stylized facts about the fertilizer market, secondly by examining the

situation of the fertilizer derivatives market and quantifying the potential

speculation (bubble) behaviour, and thirdly the interplay with food and energy

prices. In the conclusion, the main findings are summarized.

2 Literature review and hypothesis

There is a growing literature analysing recent food price developments,

commodity price formation and their interaction with market fundamentals.

Studies have analysed, among other things, the long run relationship between

fuel and food prices (e.g. Campiche et al., 2007; Yu et al., 2006; Hameed and

Arshad, 2008; Imai et al., 2008; Ciaian and Kancs, 2011), and also the price

interdependencies among different types of energy markets (Serletis and

Herbert, 1999; Asche et al., 2001; Paul et al., 2001; Asche et al., 2003;

Siliverstovs et al., 2005; Cuddington and Wang, 2006). Finally Du, Yu and Hayes

(2011) argue that speculation in the energy sector led to higher energy price

volatility which in turn spreads to the wheat and corn market after 2006.

Recently, only a few studies have focused on fertilizers: Huang (2007) for

example investigates the relationship between the long run ammonia price

elasticity and natural gas price using a cointegration analysis. Torero (2011)

examines the market structure and shows that the fertilizer industry is a global

one with a high level of concentration. For instance Trong-Tuan (2010) finds

evidence that the domestic Vietnamese price of phosphate reflects the world

price. Payne (1997) focused on the price formation of fertilizer prices and their

spatial pattern by studying the case of the urea fertilizer industry in Western

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Canada. Earlier literature on fertilizers analysed the demand (Burrell, 1980) and

supply (Anderson, 1984).

The purpose of this paper is to analyse international fertilizer prices, the factors

driving their recent fluctuation and the role of speculation, and its interplay with

the energy and commodity markets. The current literature does not cover this

topic which is surprising given the fact that fertilizers represent a key input in

agricultural production and may play an important role in explaining, partly or

fully, the recent food price increase. At the same time, fertilizers are strongly

linked to energy markets as the main input for their production is oil and gas.

There is also backward feedback from food markets to energy markets as the

agricultural sector employs energy inputs in its production process. This

triangular interdependency between the energy, fertilizer and food markets is

vital for understanding commodity price developments in general and in particular

the recent food price developments. However the interdependency with

commodity prices is not analysed in the current literature. As all these studies

only partially address fertilizers' price formation and the interdependency

between it and commodity and food prices, the aim of this paper is to examine

the following three questions:

1. The role of speculation in the formation of fertilizers' price formation. The

Homm and Breitung (2012) approach is used to identify whether there is

potential speculative behaviour on the fertilizers' physical (spot) market.

Secondly, the question whether the derivatives (future) market is a source

of speculations is investigated.

2. The interaction among fertilizer, food and energy prices. A VAR (Vector

Autoregressive) model is used to analyse the interplay between the

market prices of fertilizers, energy and commodities.

3. Fertilizer price volatility and its relation to food and energy price volatilities.

Price volatility indices are calculated to analyse fertilizer price volatility and

compare and/or contrast developments to those of the volatility of food

and energy prices.

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These three issues have dominated the discussion among policy makers and

academics in the context of the recent commodity price developments (Baffes

and Haniotis, 2010). Policy makers tend to consider speculation as a key driver

for the recent increase in commodity prices and their volatility (De Schutter,

2010). On the other hand, the academic literature is inconclusive and more

research is needed to quantify the exact contribution of speculations and market

fundamentals to the formation of commodity prices. The aim of this paper is to

shed some light on this debate by focusing in more detail on the fertilizer market.

3 Data

All data have been extracted by means of the DataM tool (Hélaine et al., 2012).

Fertilizer prices, namely world fertilizer price index, urea, potassium, phosphate,

DAP and Brent crude oil, have a monthly frequency and stem from the World

Bank. The time span dates from 1960 to 2012. The fertilizer index of the World

Bank is a weighting of nitrogen, phosphate and potassium prices. The other

World Bank indices used are the energy index, composed of the price of oil, gas

and electricity, and the grain index, composed of the price of wheat, corn,

soybean and rice. Both indices have a monthly frequency dating from 1967 to

2012. The source of food commodity prices, such as those of wheat, corn,

soybean and rice, is also the World Bank and they have the same time span and

frequency as the other indices. The source of the world production and

consumption of potash, phosphate and nitrogen is the FAO (FAO Stat); their

frequency is annual from 1993 to 2010.

4 Stylized facts

4.1 Fertilizer prices

The evolution of the fertilizer index, and the prices of the nutrients: nitrogen (N),

phosphorus (P), potassium (K) and DAP (DiAmmonium Phosphate) are depicted

in Figures 1 to 5. Fertilizer prices have increased steadily since 2002 with an

historic peak in 2008. DAP posted the largest increases – around 100% increase.

The peak in 2008 looks like the 'mathematical signature' of a bubble as defined in

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Sornete et al. (2009) or Watanabe et al. (2007): faster than exponential price

growth followed by an abrupt fall. In the next section, the quantitative analysis will

be undertaken on this question of a bubble.

For the three fertilizer components (including the fertilizer index itself) the price

peaks occur almost simultaneously. This strong co-movement in all fertilizer

components proves that the only explanation is common factors. The supply

factor, like the energy price (input cost), which enters the production process of

all fertilizer components (especially urea), seems to have triggered an initial

sharp price increase (see crude oil price in Figure 6). This might explain the co-

movement. Except the crude oil price (and to a lesser extent the exchange rate),

the world supply chain (nitrogen, phosphate and potassium) are independent of

each other (see section 4.2). The main exporters are located in different

countries: the supply of nitrogen is mainly from Russia, the supply of phosphate

from the USA, China, Morocco and Russia, and finally the potash from Canada,

Russia, and Belarus (see Table 1). This leaves the demand side elements a role

of potentially major importance. The demand for the different fertilizer

components move together because they are complements in consumption, i.e.

they are used in a given proportion to produce the fertilizer as the final output.

Indeed, the three basic plant nutrients, N, P and K are crucial to the growth of

crops. Their proportions may change depending on the soil fertility and/or the

crop itself in order to foster optimal development, but all three are necessary.

Thus, chemical fertilizers as end-products (like DAP) use all three elements

together: N, P and K with no possibility of substitution, and so the strong demand

(see Figure 7-12) and price co-movement between them is the natural

consequence.

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Fertilizer price index (World Bank)

y = 5E-06x3 - 0.0154x2 + 15.052x - 4833.1

R2 = 0.6309

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FertilizerPoly. (Fertilizer)

Price urea (World Bank)

y = 8E-06x3 - 0.0239x2 + 23.738x - 7697.3

R2 = 0.579

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US$/mt

Urea Poly. (Urea)

Figure 1: World fertilizer price index

Figure 2: Price urea (nitrogen), US Gulf

Price potassium (World Bank)

y = 8E-06x3 - 0.0239x2 + 22.999x - 7273.9

R2 = 0.6749

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Price phosphate (World Bank)

y = 4E-06x3 - 0.0115x2 + 11.264x - 3609.7

R2 = 0.4907

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Phosphate Poly. (Phosphate)

Figure 3: Price potassium, US Gulf Figure 4: Price phosphate, US Gulf

Price DAP (World Bank)

y = 2E-05x3 - 0.0679x2 + 70.211x - 23864

R2 = 0.5753

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DAPPoly. (DAP)

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y = 4E-06x3 - 0.0117x2 + 12.13x - 4146.7

R2 = 0.8377

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oil Poly. (oil)

Figure 5: Price DAP, US Gulf Figure 6: Price Brent crude oil, NYBOT

4.2 Potential factors explaining the fertilizer price

Meeting the escalating global food needs due to a growing population willing to

eat more caloric food can mainly be achieved by land area extension and/or crop

yield improvement. Given the scarcity of land, yield increase is the key source of

additional food supply necessary to satisfy future food needs. One of the main

drivers stimulating yield improvements are fertilizers. This link between yield and

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fertilizers is likely to be the main cause of the upward trend in fertilizer use

observed in recent periods and closely follows food demand expansion. Taking

into consideration these facts on food demand developments and their

interaction with fertilizers, there are four major factors that need to be taken into

account in order to understand the fertilizer prices (Figures 1 - 5): the increased

globalized structure of the world fertilizer market, the increased food commodity

demand (long-term trend and short-term demand peak), fertilizer production

costs, and concentration in the fertilizer market (market structure).

Globalization of the world fertilizer market

The fertilizer market is not exactly spatially integrated, and may differ depending

on the location (Payne, 1997). However, fertilizer prices determined in the US

Gulf, especially nitrogen and phosphate, are considered a reference for world

prices. US factors affecting world fertilizer prices have weakened over time.

Thus, the fertilizer clearing price which stems from the interaction between

demand and supply is now to an increasing degree subject to global economic

factors, including commodity prices, raw material costs and worldwide natural

resources, and energy and transportation costs, the US dollar exchange rate,

global economic development and population growth.

Nitrogen consumption

70,000

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nitrogen consumption trend

Nitrogen excess supply

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excess supply nitrogen trend

Figure 7: World consumption nitrogen (FAO)

Figure 8: World excess supply: nitrogen (FAO)

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Phosphate consumption

27,000

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Phosphate excess supply

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excess supply phosphate trend

Figure 9: World consumption phosphate (FAO)

Figure 10: World excess supply: phosphate (FAO)

Potash consumption

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excess supply potash trend

Figure 11: World consumption potash (FAO)

Figure 12: World excess supply: potash (FAO)

Total fertilizer consumption

118,000

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total fertilizer consumption trend

Total fertilizer excess supply

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excess supply total fertilizer trend

Figure 13: World consumption total fertilizer (FAO)

Figure 14: World excess supply total fertilizer (FAO)

The global consumption of fertilizer nutrients since 1993 is depicted in Figures 7,

9, 11 and 13. The graphs also indicate the trend until 2007 when the peak

occurred. From 1993 to 2007 fertilizer consumption (nitrogen, phosphate, and

potash) increased at an annual growth rate of 2.4%, 2.6% and 3.6% respectively.

China and India imported increasing quantities of fertilizers over time to meet the

rising food demand. The influence of these two countries on global fertilizer

prices is growing. For the same period of time, nitrogen, phosphate and potash

- 13 -

production rose at a rate of 1.8%, 2.2% and 4.1% per year respectively. These

percentages indicate the imbalance between supply and consumption, especially

for nitrogen and to a lesser extent phosphate. Figures 8, 10 and 12 depict the

difference between the world supply and demand (called 'excessive supply') for

each nutrient and also for the aggregate (Figure 14). The gap between supply

and demand widened for nitrogen in particular but also phosphate as indicated

by the downward sloping trend. The strong growing demand could only be

matched by making use of and thus reducing the stock of fertilizer nutrients.

Meanwhile, the stocks of potash have increased according to the data for the last

15 years. This is the reason why the peak for potash prices occurred later

(beginning of 2008). It seems obvious that phosphate and especially nitrogen

pushed up phosphate prices due to their complementary nature within the

fertilizer sector. It appears that the potash sector was not responsible of the

overall price peak in the fertilizer sector.

High commodity prices

What are the reasons for this strong demand for fertilizers? The demand for

fertilizers depends directly on the situation of the commodity market. As can be

seen in Figure 15, fertilizer and food commodity prices follow the same pattern

and the two markets are inter-related. More recently, western government

policies by implementing biofuel mandates added an important factor in the

demand for food commodities, especially for corn (ethanol) and oilseed (bio-

diesel) (see e.g. Diffenbaugh and al., 2012). For instance the expansion of

ethanol production in the US has led to an increase in the planting of corn at the

expense of soybeans and wheat. Corn production is more demanding in terms of

nitrogen than soybeans and wheat. Furthermore, the biofuel programmes have

increased the interdependence between food commodity prices and energy

prices (see Du et al., 2011). The energy prices are the primary cost of the

nitrogen production. This suggests that it is likely that the commonality between

fertilizers and commodities might increase over time as long as bio-fuel

production expands.

- 14 -

Prices

0

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wheh corn all fertilizers Nitrogen Phosphate

Figure 15: Grain prices (wheat and corn) and fertilizers (N and P)

Furthermore, since 2007 the global supply of commodities has experienced a

series of adverse weather shocks: drought and floods in Australia, drought in

Ukraine, fires in Russia, extended dry spell in the north-western area of the EU in

the spring, cool wet weather in the US Corn Belt, floods in Thailand, El Niño in

the Pacific etc. These fundamental supply shocks coupled with the strong

demand lowered the stock of commodities and eventually provoked historical

price peaks in commodity prices in 2007-2008 (see Figure 15). Although

commodity prices have decreased since they are still above average. High

commodity prices lead to larger marginal revenues of agricultural production

which drive up fertilizer prices. In response to high commodity prices farmers

expanded their land use by around 5 million hectares at world level. High

commodity prices also encourage farmers to increase their fertilizer application

rate in order to increase the quantity of the output. The total fertilizer demand

(nitrogen) was around 172 (100) Mtons in 2007 compared to 140 (83) Mtons in

average between 1993 and 2007. This historically high demand in 2007 led to

the lowest level of inventory of fertilizers in the last 15 years, as depicted in

Figure 14 (Figure 8).

- 15 -

Production costs

On the production side of the fertilizer market, the input costs put upward

pressure on fertilizer prices. Chemical fertilizer production is an energy intensive

process and requires large amounts of energy. Ammonia used to produce urea

and nitrate is particularly energy dependent. Nitrogen as a raw material (78%

volume in the atmosphere) is available almost without limit but its transformation

into ammonia (Haber-Bosch process) is highly demanding in terms of energy,

particularly natural gas. Natural gas accounts for 72-85% of ammonia production

costs according to Huang (2007). In addition, the costs of shipping ammonia (as

a hazardous material transported in pressurized containers) are relatively high,

e.g. transport costs represent 50% of the cost of ammonia shipped from Russia

to the US Gulf (Huang, 2007). Although phosphorus and potassium production is

less demanding in energy, the extraction of phosphorus from phosphate rock and

potassium from potash represents an important cost item in addition to the

transportation costs. Energy prices (gas and oil) have been experiencing an

upward trend since the beginning of the 2000s (between 1999 and 2008 natural

gas prices increased by more than 550% and oil by 970%) with a peak in 2008,

which in turn has made the fertilizer cost higher (see Figure 6).

A highly concentrated fertilizer market

The structure of the fertilizer market may also explain a part of the story related

to its price formation and vulnerability to fluctuations. Trade in fertilizers has been

growing in the USA and Europe for the last 20 years. The international fertilizer

prices set in the US Gulf depend more and more on international factors. China

is now the largest importer of potash followed by the USA. Also the supply chain

is integrated on a world scale. The fertilizer market is now global. Some local

events provoke peaks in internal fertilizer prices. For instance, in 2007, the value

of the Moroccan phosphate rock contract increased by almost 350%, while the

international price of sulphur grew by almost 200%, and the ammonia price

doubled (US Gulf). Thus, the costs of raw material to produce DAP (DAP is

produced by means of phosphate rock, sulphur and ammonia) in Europe doubled

in just a couple of months. This example illustrates how the fertilizer industry is

- 16 -

linked at world level. Supply chains gained in efficiency but became more

vulnerable to international shocks. This world integration of the fertilizer industry

leads to a 'just in time' supply practice in order to lower inventory costs (which

are very high for fertilizers). Low stocks of raw fertilizers in Europe or the USA

makes the fertilizer industry very vulnerable to unexpected shocks since they

translate immediately into price peaks.

High rates of internationalization also increased the competition within the

fertilizer sector. The rationalization of the fertilizer industry was essentially made

through mergers of production factories. Today, much of the industry is very

concentrated with only a few large suppliers (firms, associations). For instance in

the USA, only 7 firms produce phosphoric acid and only three companies control

80% of the production of phosphoric acid (Huang (2009). In Canada and Russia

the export of potash also depends on one single association. Thus, the global

phosphate and potash fertilizer marketing is highly concentrated. This market

structure is prone to non-competitive price setting. Concentration is also seen

regarding the location of the raw materials for fertilizers. Potassium reserves are

owned by a few countries and companies; two thirds of world production takes

place in Canada, Russia, and Belarus; and only 8 companies control 80% of the

production. Ammonia is produced mostly in Russia, Ukraine and Trinidad and

Tobago (Malingreau et al., 2012). The USA and China dominate the supply of

phosphate. The top six countries controlling more than two thirds of the world's

production capacity of all major fertilizer products are summarized in Table 1.

Table 1: Percentage of world share of fertilizer production (FAO, year 2007 in Mtons) Nitrogen % Phosphate % Potassium %

China 34.2 China 32.4 Canada 31.3 India 10.1 USA 25.6 Russia 21.1 USA 8.2 Russia 6.5 Belarus 14.8 Russia 7.0 India 6.3 Germany 8.4 Indonesia 2.9 Morocco 2.7 China 5.8 Ukraine 2.6 France 1.0 USA 3.2 Top 6 73.0 Top 6 77.0 Top 6 84.6

This highly integrated fertilizer supply largely depends on the internal flow

functioning well. The trade policies of the major players impact directly on the

- 17 -

world price of fertilizers. China imposed a special tariff rate (export tax) of 100%

on fertilizers to lower the volume of exports. Consequently, the international price

of DAP increased by about 185% according to Huang (2009) because China is

the second largest exporter of phosphate and the largest exporter of urea. Some

indirect measures also distort world trade allocation: for instance in India the

government subsidises the use of fertilizer, which fosters imports as most of the

fertilizers are imported. To conclude, Chinese and Indian government activated

trade policy measures (decrease exports and increase imports) to provide their

farmers with enough fertilizer, thus provoking even higher world prices.

5 The role of speculations in fertilizer price formation

This section attempts to investigate the importance of speculations in

determining fertilizer price developments. First the occurrence of speculations on

the fertilizer market is estimated and second the potential source in the

derivatives market is investigated. Speculative behaviour is seen by many market

analysts, as well as by policy makers, as a key driver of recent price

developments on commodity markets (De Schuster, 2010). According to Stiglitz

(1990), a speculator can be defined as an agent who buys an asset or

commodity expecting to sell it at a higher price without being concerned about

market fundamentals. The behaviour of speculators might be caused by trading

techniques like technical extrapolation, herding behaviour or moral hazard (in the

event of a public bail-out the agent does not bear the entire risk and so adopts an

excessive risk investment). In contrast, the 'investor' is considered a

'fundamentalist'. The price of an asset or commodity which does not reflect

fundamentals (its intrinsic value based on fundamental factors) over several

years is considered a period of a 'price bubble' or 'speculative bubble'. The price

misalignment is caused by speculators who do not invest relative to the

'fundamental factors' but believe that the selling price will be higher and still

beyond its fundamentals (Stiglitz 1990). The literature on asset price bubbles is

vast, and there are many different approaches to modelling bubbles. The first

type of model is the so-called rational bubbles proposed by Blanchard and

Watson (1982). The second type of model is the agent-based type where the

interaction between trend following "chartist" and "fundamentalist" explain the

- 18 -

price dynamic (Day and Huang (1990). Finally, a physics inspired model leading

to super-exponential growth has been developed by Derman (2002). Empirically,

the challenge of all these models is to detect the 'intrinsic' (fundamental) value of

a commodity. A model must be very well specified otherwise the estimates may

be misleading. Sophisticated econometric tools and sufficiently detailed data are

necessary to disentangle what belongs to a bubble movement from the

underlying fundamental factors.

Given these difficulties, econometric tests have been developed to detect

bubbles. Some econometricians like Homm and Breitung (2012) argue that it is

more realistic to directly observe the raw price (without a factor model) and to

observe the bubble ex-post. Homm and Breitung (2012) and Phillips, Wu and Yu

(2011) assimilate the emergence of a bubble with the date of a regime switch

from a random walk to an explosive process. A random walk is characterized by

having an autoregressive coefficient of one (Yt+1 = Yt + Xt, with xt niid(0,1)),

whereas the explosive process has an autoregressive coefficient larger than one

(Yt+1 = bYt + Xt, with b>1 and Xt niid(0,1)). Thus, the signature of the bubble is an

explosive price rise followed by an abrupt price collapse. Here again, this is an

interesting approximation because an abrupt price fall for instance should only be

considered as the bursting of a bubble if no new information concerning supply or

demand appears.

- 19 -

Table 2: Unit root tests adapted by Homm and Breitung (2012) Test Statistics Critical valuesa Bubble period 90% 95% 99% Begin End Fertilizer index Watanaba&Takaysu 08/2007 11/2009 Phillips&Wu&Yu rec_d 11.0*** 2.26 2.59 3.24 Yes - Chow type sup DFC 0.63NS 1.57 1.9327 2.62 04/2002 Brusetti&Taylor sup BT 2.29* 1.9317 2.47 3.88 05/2006* 11/2009 Urea Watanaba&Takaysu 11/2007 12/2008 Phillips&Wu&Yu rec_d 3.6145*** 2.2610 2.5958 3.2400 Yes - Chow type sup DFC -0.6297NS 1.5762 1.9327 2.6285 06/1999 Brusetti&Taylor sup BT -0.9750NS 1.9317 2.4748 3.8878 10/1998 12/2008 Potassium Watanaba&Takaysu 01/2008 05/2010 Phillips&Wu&Yu rec_d 15.2385 2.2610 2.5958 3.2400 Yes - Chow type sup DFC 0.9310 1.5762 1.9327 2.6285 10/1986 Brusetti&Taylor sup BT 3.3775 1.9317 2.4748 3.8878 07/2003 05/2010 Phosphate Watanaba&Takaysu 09/2007 09/2009 Phillips&Wu&Yu rec_d 8.9475 2.2610 2.5958 3.2400 Yes - Chow type sup DFC -0.6310 1.5762 1.9327 2.6285 06/1977 Brusetti&Taylor sup BT 1.9592 1.9317 2.4748 3.8878 12/2006 11/2009 DAP Watanaba&Takaysu 10/2007 03/2009 Phillips&Wu&Yu rec_d 7.9691 2.2610 2.5958 3.2400 Yes - Chow type sup DFC -0.3354 1.5762 1.9327 2.6285 03/1986 Brusetti&Taylor sup BT 1.7952 1.9317 2.4748 3.8878 08/2000 03/2009 (a) Critical values with trend

5.1 Identification of speculations (bubbles)

The approach of Homm and Breitung (2012) to identify whether there is a bubble

on the physical (spot) fertilizers market is adopted. Their approach consists of

testing for the existence of an explosive process in fertilizer prices (i.e. whether

the autoregressive coefficient is larger than one). Three unit root tests adapted

by Homm and Breitung (2012) are performed on the monthly prices of the

fertilizer index, urea, phosphate, potassium, and DAP. The null hypothesis of all

tests is that the price series is I(1) against an I(1) process which experiences a

regime switch to an explosive process. The three tests are derived from Phillips,

- 20 -

Wu and Yu (2011): a recursive Dickey Fuller test, a Brusetti and Taylor (2004)

and a Chow type test with structural break. The results of the tests are reported

in Table 2. Phillips, Wu and Yu's test detects a bubble in all fertilizer prices. The

Brusetti and Taylor test detects potassium and phosphate (at 90%). This reveals

the potential existence of bubbles in fertilizer markets.

Since the Phillips, Wu and Yu do not inform on the beginning and end of the

bubble, the Watanabe and Takayasu and Takayasu (2007) method was

performed in order to detect the exact timing. Figures 1 to 5 depict the nominal

prices of the fertilizer, their quadratic trend, and the period of the bubble (dashed

area) according to the bubble timing of the Watanabe, Takayasu and Takayasu

(2007) method. The graphs show that fertilizer prices experienced a price bubble

(explosive) followed by an abrupt fall. Urea, phosphate and DAP experienced the

beginning of the bubble in late 2007 and potassium in January 2008. Potassium

was the last to be affected certainly because it is less energy dependent. Energy

prices have triggered a rise in the price of nitrogen, which in turn dragged up the

price of the other components due to their complementary nature as explained in

section 4. Common expectations for every fertilizer component (due to their

complementarities) might have followed for the whole fertilizer market. This

explains the simultaneity of price bubbles among the fertilizer components.

According to the tests, the fertilizer market might have experienced a bubble.

However, the evidence is not conclusive as not all tests (depending on the

fertilizer) were significant. The next section examines whether the derivative

(future) markets can explain the potential bubble (if any). First the relationship

between derivatives and the physical (spot) fertilizers' market is described. Then

the effects of speculations are measured. The derivative market is the focus point

as it was identified in some literature as the main source of speculations (De

Schutter, 2010 and Robles et al. 2009). The potential cause of a bubble coming

from other sources such as the physical market itself, as well as from other

markets such as energy and food, is not investigated in this study.

- 21 -

5.2 Relationship between derivative and physical fertilizers market

The fertilizer market (like the commodity market) has a derivatives market.

Currently the only type of derivative product available to hedge against price

swings of fertilizers are off-exchange market derivatives (OTC: Over The

Counter). Two major brokers provide fertilizer SWAPS: Direct Hedge based in

Copenhagen and FIS (Freight Investor Service) located in London. These

brokers offer SWAPS for four major fertilizer underliers: nitrogen (urea & UAN),

DAP and Ammonia. The broker facilitates a tailored agreement between buyers

and sellers. All fertilizer SWAPS are cash-settled (no physical delivery). At

maturity, the difference in price between the fertilizer index of the given underlier

and the future price agreed upon previously will be cashed in by the buyer or the

seller, called cash-settled vanilla SWAP. Currently, Direct Hedge and FIS

fertilizer SWAPS establish cash-settled fertilizer SWAPS of roughly 6 million

metric tons (Mtons) per year (for all types of underliers).

The major broker in the fertilizer insurance market is Direct Hedge which, since

2000, offers fertilizer SWAPS. At the beginning of 2000, the volume traded was

around 200 000 metric tons of fertilizers. The fertilizer indices used by Direct

Hedge are: urea granular bulk US Gulf, UAN US nola, DAP Bulk tampa US gulf,

and DAP Bulk nola fob. As the volume traded has increased the exposure to

settlement risk credit risk has grown in parallel. The requirement for a credit-

secure derivatives trading environment has developed in the fertilizer market. As

a result, since July 2011, Direct Hedge introduced four types of standardized

SWAPS (100 metric tons) into the CME clearport to ensure the clearing and

settlement. These four SWAPS are: urea granular bulk, UAN fob nola, DAP fob

Tampa, and DAP fob nola.

The second most important broker also active in offering fertilizer SWAPS is FIS

which has only been active since 2005. The FIS Fertilizer SWAP is settled

against the respective Fertilizer Index. The Fertilizer Index is a single reference

price calculated from three weekly price ranges provided by FertilizerWEEK,

FERTECON and FMB using a simple averaging technique. The volume traded

- 22 -

by FIS is lower but has also grown very rapidly in recent years. For the same

reason, FIS introduced SWAPS to the LCH (London Clearing House).

5.3 Interaction between future and physical market

Derivatives are contracts whose price depends on the factors which drive the

price of the commodity (physical). A priori, the future price depends on the

expectations of the market participants regarding the market prospects in the

future (level of stock prices, supply and demand). The derivative market helps

the price discovery of the spot price. The difference between the expected spot

at the maturity of the derivative contract and the forward price should only be the

cost of carry (price of time: interest rate, the storage cost of warehousing,

insurance, depreciation) minus the convenience yield (benefit from physical

holding). However, future prices can affect the spot price via the physical stocks.

For instance if the future prices are much higher than the spot prices

(backwardation), stores will increase their inventories which drives up the spot

price, and vice versa. The consequence of this mechanism is a lowering of the

spot price swings. This is the first reason why derivative markets decrease

volatility regardless the players on the derivative markets are speculators or

hedgers. Moreover, as shown by Turnovsky (1983) and Torricelli (1993), the

existence of a derivative market increases the level of inventory in the long-term.

Indeed, suppose a commercial hedger (for its physical stock) needs a

counterpart to hedge it, and there is no hedger accepting the risk (counter

position), the commercial hedger eventually would not store, or store less or even

quit the business because he is risk-averse. In the opposite case, a liquid

derivative market will ensure the commercial hedger to find a counterpart, which

can be a hedger or a speculator as they do the same job. A liquid derivative

market leads to larger stocks, which in turn lowers the volatility, as it can act as a

buffer to mitigate supply (or demand) shocks. Speculators help to increase the

liquidity of the market. Figure 15 shows the volatility of fertilizers since 1974.

There is no sign of volatility increasing since the introduction of fertilizer swaps.

However, the volatility of urea exhibits a positive trend since the 2000s but this

tendency parallels the increase in energy commodity volatility.

- 23 -

Moreover, the tendency of volatility to increase in the fertilizer market recently

cannot be attributed to the introduction of the derivative markets in the energy

sector since they were created several decades ago. Most of them were

established at the beginning of the 1970s: Heating oil NYMEX futures, 1978; Gas

oil IPE futures, 1981; NYMEX WTI in 1983, Brent crude IPE, 1988; natural gas

IPE futures, 1997 etc..

5.4 Measuring speculative activity in the derivative market

Contrary to the stock market (secondary) the derivative market is by nature a

hedging market (risk management tool). Consequently, speculation is more

difficult to evaluate because there is a need to differentiate between speculation

and non-speculation. It is obvious that the price of the contract will change if the

expectations of the price change of the underlier, and so speculation is also

possible. Working (1960) proposes that commercials (traders who are in the

agro-business) be considered as 'hedgers' since they have to hedge their real

activity, whereas non-commercials are considered as 'speculators' with no

hedging needs. However, since there is rarely a balance between short hedgers

and long hedgers, speculators have a vital role to allow the agro-business to

hedge. The question is whether there is 'excessive' speculation (including index

investment) relative to commercial hedging needs in the agricultural markets. If

there is more speculation than is required for commercial hedging needs, then

the derivative market becomes one of speculators trading with other speculators.

Consequently, to measure speculative behaviour, Working (1960) defines the T

index as follows:

T= 1 + SS/ (HL + HS) if HS > HL

or T = 1 + SL (HL + HS) if HL > HS,

where open interest held by speculators (non-commercials) and hedgers

(commercials) is denoted as follows: SS = Speculation Short; HL = Heading

Long; SL = Speculation Long; HS = Hedging Short.

The intuition behind this index is straightforward to understand. The denominator

is the total amount of futures open interest due to hedging activity. If the amount

- 24 -

of short hedging is greater than the amount of long hedging, then speculative

longs are needed to balance the market; and technically, speculative shorts are

not required by hedgers. Any surplus of speculative short positions would thereby

need to be balanced by additional speculative long positions. The speculative

short positions would then be superfluous, or 'excessive'. Thus, the speculative T

index measures the excess of speculative positions beyond what is technically

needed to balance commercial needs, and this excess is measured relative to

commercial open interest. The T index can tell us whether trading speculative

derivatives are excessive relative to commercial hedging needs.

Unfortunately, fertilizer SWAPS have only recently been cleared on the CBOT

and LCH. Moreover, neither the US CFTC nor the EC inform of the origin of the

market players regarding fertilizer SWAPS. The information should be held by

Direct Hedging and FIS Fertilizer. If they do not provide this information, the

'excessive' speculation on the derivative market cannot be quantified. According

to practitioners in the fertilizer SWAP industry, most of the traders on derivatives

are also active on the physical market. Furthermore, the world production of

nitrogen, phosphate and potash equals 154 200, 43 300 and 43 213 (1000

Mtons) respectively according to the FAO. The volume traded on the derivative

market is around 6 000 (1000 Mtons) which is equivalent to a gearing of about

0.024%. According to these figures, the volume traded on the derivative market

is marginal compared to the one traded on the physical market. If it is supposed

that the size of the derivative market (trading volume) indicates a market power

over the determination of the sport price, then it is hardly credible that open

interests on the derivative market can be blamed for the bubbles on the fertilizer

market.

6 Price interaction between fertilizers, food and energy

In this section we attempt to examine the interplay among fertilizer prices, energy

prices and commodity prices. More specifically we examine to what extent food

and energy prices play a role in fertilizer price formation. All their markets are

interlinked and thus their prices affect each other. Firstly, fertilizers are linked to

energy markets because the main input for their production is oil and gas.

- 25 -

Secondly, fertilizers enter as an input into agricultural production and affect the

productivity of the agricultural sector. More importantly, the use of fertilizer

increases as the price of commodity prices increases. Finally, there is feedback

from the food market to the energy market through its demand for energy in

agricultural production (e.g. fuel). The exact causal relationship between the

three markets is an empirical question as it depends on many factors such as the

size of the respective market, market structure, etc. To empirically identify the

direction of causality between fertilizer, food and energy prices the Vector

Autoregressive (VAR) model and the accompanying Granger causality test

(Granger, 1969) is employed.

6.1 VAR analysis

Because prices are interdependent, applying a standard regression approach

would violate the exogeneity assumption of regressors. A general method to

analyse interdependences between endogenous variables is the VAR model

whereby the causality between the current and past values of the variables is

examined. The general specification of the VAR, measuring the interplay

between fertilizer, energy and food markets, is represented as follows:

ttttt eyAyAyAcy 332211 ,

where y is the vector of variables (prices), A1 , A2 and A3 are the matrix and c the

vector of the parameters, and their dimension depends on the number of

variables, and e are the residuals.

The specification of the VAR which is proposed hereinafter is a compromise

between the number of variables and the number of lags. The addition of lags

and variables leads to a larger number of coefficients to be estimated, which

reduces the power of the estimates. The classical time series unit root tests were

performed: ADF (Augmented Dickey-Fuller, 1981), the PP (Phillips-Perron, 1988)

and the ERS (Elliott-Rothenberg-Stock, 1996). The first difference of logarithm

was used for each time series in order to ensure stationarity. The maximum of

lags chosen were set to 3, and the lag structure is based on the SBCI (Schwartz

Bayesian Information Criteria).

- 26 -

The sample used has a monthly frequency, with a time span from 1967 to 2012,

which gives 536 observations per variable. Three specifications of the model are

set. In the first specification (1), price indices are used for the vector of variables

y: energy index, grain index fertilizer index of the World Bank. Using an index has

the advantage of reducing the number of variable series and so the number of

coefficients to be estimated. In the other two specifications, specific energy and

fertilizer prices were used, oil price, dap, urea, potassium, phosphate, instead of

global indices. Also instead of using the grain index, the prices of wheat, corn

and soybean were used. The problem is that with three lags, the number of

coefficients to be estimated increases exponentially if all these specific prices are

included in the VAR and the estimation becomes intractable. For this reason a

compromise solution is chosen where only selected prices are included. Thus, in

specification (2) energy, fertilizer, dap and grain were included into the vector of

variables y. In specification (3), oil, dap and grain price were included in the

vector of variables y.

The VAR was completed with the Granger causality test (Granger, 1969). The

Granger causality test examines the causality between variables of interest.

Under the null hypothesis, the variable (A) does not Granger-cause variable(s)

(B). Thus, under the alternative hypothesis, the variable (B) Granger-causes (B),

which means that variable(s) (B) can be better predicted using the past values of

both variable (A) and variable(s) (B) than it can be using variable (B) alone.

VAR results

The results of the Granger causality test are reported in Table 3. The causality

tests clearly reveal that energy prices (costs) caused an increase in the price of

fertilizers and commodity prices. However, the increase in commodity prices

preceded the increase in fertilizers. Thus, the increase in commodity prices

provoked an increase in fertilizer prices, and not the opposite.

- 27 -

Table 3: Granger causality between the fertilizer, commodity and energy prices VAR variables (prices):

(A) (B) Chi χ2

dof* p-val. H0 Con-clusion

(1) energy fertilizer, grain 19.12 6 0.00 Reject at 1% (A) => (B) (2) energy fertilizer, dap, grain 14.81 6 0.02 Reject at 5% (A) => (B) (1) grain fertilizer 6.29 3 0.09 Reject at 10% (A) => (B) (2) fertilizer energy 0.60 2 0.74 No rejection (A) ≠> (B) (2) fertilizer grain 25.41 2 0.00 Reject at 1% (A) => (B) (2) dap grain 27.44 2 0.00 Reject at 1% (A) => (B) (2) energy grain 12.95 2 0.00 Reject at 1% (A) => (B) (3) grain oil 1.33 2 0.52 No rejection (A) ≠> (B) (*) degree of freedom

7 Fertilizers price volatility

This section expands on the previous analysis by examining fertilizers' price

volatility. Its aim is to explore how fertilizers' price volatility evolved over time

compared to the volatility observed in the food and energy markets. A prevalent

perception is that volatility in commodity markets has increased in recent years,

in particular when related to food and energy prices as proved in the chapters of

Piot-Lepetit and M'Barek (2011). Furthermore, Baffes and Haniotis (2010) show

that all commodities were affected by the volatility increase in 2007-08

(compared to the 1972-73 crisis) proving that the link between energy and non-

energy commodities (food particularly) is nowadays stronger. Hereinafter, the

similarities and differences of the volatility of fertilizer prices with respect to food

and energy prices are analysed. To measure price volatility two indices were

calculated. First, the volatility is measured as the standard deviation of the

monthly return over one year with no overlap (no rolling window), the measure is

annualized (multiplied by the square root of 12). However, to understand more

precisely the co-movement of volatility between the energy sector and the

different fertilizer components, the volatility was recalculated as depicted in

Figure 17. Measuring volatility with no overlaps from one year to the next has the

advantage that every volatility observation is independent. The drawback

however is that it is difficult to assess the timing (which volatility precedes)

among the different volatilities. As a result, a rolling-window of one month was

applied (Figure 17).

- 28 -

The evolution over time of the volatility of energy, fertilizers and food from 1960

to 20012 is depicted in Figure 16 (World Bank indices). It shows that food

volatility is, on average, much lower than others volatilities (fertilizer, energy).

Although food also experienced a volatility increase during the petrol crisis of

1973-74 and the commodity crisis of 2007-08, the volatility of fertilizer follows the

volatility of energy (and oil) much more closely. Indeed, during the two historical

commodity crises (1973-74 and 2007-08) the volatility jumps in energy and

fertilizers are alike. However, the volatility increase in energy in 1986 and 1990

did not spread to the fertilizer market. The volatility increase in the energy sector

was due to a strong price fall. This indicates that fertilizer and energy volatility

move together when the volatility increase happens in an environment of rising

energy prices. Interestingly, prior to the first oil price shock, the volatility of

energy was much lower whereas afterwards the volatility of energy is

systematically larger than fertilizer and especially food volatility.

Annualized volatility

0

20

40

60

80

100

120

1960

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

Source: own calculation; data World Bank

%

vol_energy vol_food

vol_fertilizer vol_metal

vol_dow jones

Figure 16: Annualized volatility of energy, fertilizer and food (no rolling window) In this paragraph, the different components of fertilizers are analysed. The

volatilities of urea and energy (or oil) have the strongest correlation over time

among all fertilizer nutrients. This phenomenon is explained by the fact that most

of the input of urea is energy (see section 4.2). Potassium, but also phosphate,

- 29 -

has a much lower volatility and their volatility is much more independent of the

energy price volatility. DAP and fertilizer index volatility are very similar, which is

normal as both contain nitrogen, phosphate and potassium. The volatility of urea

is much higher on average than that of the other fertilizer components; it seems

obvious that its high dependence on the energy sector is the most plausible

explanation, especially when the volatility of energy is increasing proportionally to

rising energy prices. Finally, the volatilities experienced in the fertilizer and

energy sectors during the first oil price shock in 1973/74 were higher (and

shorter) than during the commodity crisis of 2007/08 where there are no peaks

but the increase is longer lasting. Since the mid-2000s, the volatility has been

increasing in the fertilizer and energy markets and for now shows no signs of

decreasing.

Volatility fertilizers

0

20

40

60

80

100

120

140

160

Jan-

74

Jan-

76

Jan-

78

Jan-

80

Jan-

82

Jan-

84

Jan-

86

Jan-

88

Jan-

90

Jan-

92

Jan-

94

Jan-

96

Jan-

98

Jan-

00

Jan-

02

Jan-

04

Jan-

06

Jan-

08

Jan-

10

Jan-

12

annualized & in %

fertilizer urea potassium phosphate

dap oil energy

Figure 17: Annualized volatility of fertilizer and oil and food (rolling window)

8 Conclusion

This study analyses the drivers behind the recent price evolution of fertilizers and

their interplay with energy and food commodity market prices. This study focuses

on three issues that shape the current debate on commodity price developments:

- 30 -

(i) the role of speculations (bubbles) for fertilizers price formation and (ii) the

interaction among fertilizers, food and energy prices and (iii) fertilizers price

volatility.

First, evidence of speculative behaviour on fertilizer markets is found. However,

speculation on derivative markets can hardly be considered as the cause.

Indeed, the volume of the fertilizers' derivative market is marginal (6 Mtons in

total) compared to the physical market (170 000 Mtons of fertilizers consumed).

This argument holds if one believes that the amount of volume traded indicates a

kind of market power of the derivative market over the spot market. In that case,

the recent rapid expansion of this new derivative market might instead be due to

the growing volatility of international fertilizer prices, especially urea, and it is

probable that most of the fertilizer derivative products may be used as hedging

tools and not as speculative ones. The co-movement of prices in the derivative

and physical markets just show that they are driven by the same fundamental

factors. Some authors might have been misled when believing that the prices on

the derivative market lead the physical market; high correlation does not mean

causality. On the contrary, the peak in fertilizer prices first occurred on the

physical market due to the uncertainty of the grain and fertilizer markets (high

volatility). However a potential cause of bubbles coming from other sources such

as the physical market itself or other factors have not been analysed yet.

Furthermore, further research should be conducted to see if speculation outside

the fertilizer sector (i.e. in food and energy markets) may have partly induced the

price increases and volatility of fertilizers.

Second, the prices of food commodities have influenced the fertilizer market and

not vice versa. Our results show that there is substantial co-movement between

fertilizers' and food prices, but that the food prices are among the causes of the

fertilizer price movements. In addition, higher food prices induced a higher

demand for fertilizers, again boosting prices to higher levels.

Third, the energy sector triggered the increase in fertilizer prices through the

input cost channel. Energy represents a key input in the production of fertilizers.

Rising oil and natural gas prices provoked a spark for the nitrogen nutrients

- 31 -

whose production depends heavily on energy inputs for production and transport.

The same occurred to phosphate and potash, where energy input is less

important in their respective production cost structures.

Fourth, given the oligopolistic fertilizer supply chain and the inelasticity of the

supply of fertilizers (there is a 5 to 10 year delay before new production plants

can be put into the supply chain), this created an upward adjustment of the

expectations in the fertilizer market causing an upward spiral effect of the price.

This eventually might have provoked a price peak in 2007 due to the uncertainty

surrounding the low levels of global fertilizer stocks (nitrogen and phosphate).

Over the previous 15 years, the excess nitrogen supply has nearly vanished

while phosphate and potash have remained at marginal levels, meaning that no

buffer could protect the market when an adverse shock occurred in 2007.

Finally, the volatility of energy, food and fertilizer prices move closely together in

an environment of rising energy prices. In the opposite scenario, food and

fertilizer volatility do not move together with the volatility of energy prices in an

environment of decreasing energy prices. Consistent with other studies, the

volatility of fertilizer, energy and food prices is lower during the commodity price

peak of 2007/08 than during the 1973/74 oil price shock.

- 32 -

References

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Robles, M., Torero, M., von Braun, J. (2009). When speculation matters, IFPRI (International Food Policy Research Institute) Issue Brief 57. Miguel Robles, Maximo. Saravia-Matus, S, Gómez y Paloma, S., Mary S. (2012). Economics of food security: selected issues, Bio-based and Applied Economics, forthcoming. Serletis, A., Herbert, J. (1999). The Message in North American Energy Prices. Energy Economics 21, 471–483. Sornette, D., Woodard, R., Zhou, W-X. (2009). The 2006-2008 oil bubble: evidence of speculation, and prediction, Physica A, 388, 1571-1576. Stewart, W.M.; Dibb, D.W.; Johnston, A.E.; Smyth, T.J. (2005). The Contribution of Commercial Fertilizer Nutrients to Food Production". Agronomy Journal 97, 1–6. Stiglitz, J. (1990). Symposium on Bubbles. Journal of Economic Perspectives 4: 2. Torero, M. (2011). Fertilizer market situation: market structure, consumption and trade patterns, and pricing behaviour. IFPRI Discussion paper 01058. Trong-Tuan, L. (2010). Phosphate Fertilizers’ Domestic Price Movement in Vietnam. International Journal of Business and Management Vol. 5, No. 5. United Nations Secretariat, (2011). World Population Prospects: The 2010 Revision. Highlights. New York: United Nations Watanabe, K., Takayasu, H., Takayasu, M. (2007). A mathematical definition of the financial bubbles and crashes, Physica A. 383, 120-124. Wolf, H. (2005). Volatility: Definitions and consequences, in Managing Economic Volatility and Crises, ed. by Aizenman, J. & Pinto, B. Cambridge University Press Working, H. (1960). Speculation on hedging markets. Food Research Institute Studies, Vol. I, No. 2.  

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European Commission 

EUR 25392 – Joint Research Centre – Institute for Prospective Technological Studies 

 

Title: Fertilizer markets and their interplay with commodity and food prices 

 

Author(s): Hervé Ott 

 

Luxembourg: Publications Office of the European Union 

 

2012 – 36 pp. – 21.0 x 29.7 cm 

 

EUR – Scientific and Technical Research series –ISSN 1831‐9424 (online) 

 

ISBN 978‐92‐79‐25526‐7 (pdf) 

 

doi:10.2791/82136 

 

 

 

Abstract 

 

This study analyses the drivers behind the recent price evolution of  fertilizers and their  interplay with energy and 

food  commodity market  prices.  First,  evidence  of  speculative  behaviour  on  fertilizer  markets  is  found.  However, 

speculation on derivative markets  can hardly be  considered as  the  cause. The  recent  rapid  expansion of  this  new 

derivative market might be due  to  the growing volatility of  international  fertilizer prices, especially urea, and  it  is 

probable  that most of  the  fertilizer derivative products may be used as hedging tools and not as speculative ones. 

Indeed,  the peak  in  fertilizer  prices  first  occurred on  the physical market  due  to  the  uncertainty  of  the  grain  and 

fertilizer markets (high volatility). Second, the prices of food commodities have influenced the fertilizer market and 

not vice versa. The results show that there is substantial co‐movement between fertilizers' and food prices, but that 

the food prices are among the causes of the fertilizer price movements. Higher food prices induced a higher demand 

for fertilizers, again boosting prices to higher levels. Third, the energy sector triggered the increase in fertilizer prices 

through the input cost channel. Energy represents a key input in the production of fertilizers. Rising oil and natural 

gas  prices  provoked  a  spark  for  the  nitrogen  nutrients  whose  production  depends  heavily  on  energy  inputs  for 

production and transport. The same occurred to phosphate and potash, where energy input is less important in their 

respective production cost structures. Fourth, given the oligopolistic fertilizer supply chain and the inelasticity of the 

supply of fertilizers (there is a 5 to 10 year delay before new production plants can be put into the supply chain), this 

created  an  upward  adjustment  of  the  expectations  in  the  fertilizer market  causing  an  upward  spiral  effect  of  the 

price. This eventually might have provoked a price peak in 2007 due to the uncertainty surrounding the low levels of 

global fertilizer stocks (nitrogen and phosphate). Over the previous 15 years, the excess nitrogen supply has nearly 

vanished while phosphate and potash have  remained at marginal  levels, meaning  that no buffer  could protect  the 

market when an adverse shock occurred in 2007. Fifth, the volatility of energy, food and fertilizer prices move closely 

together in an environment of rising energy prices. In the opposite scenario, food and fertilizer volatility do not move 

together with  the volatility of  energy prices  in an environment of decreasing energy prices. Consistent with other 

studies,  the volatility of  fertilizer, energy and  food prices was  lower during  the commodity price peak of 2007/08 

than during the 1973/74 oil price shock. 

As the Commission’s in‐house science service, the Joint Research Centre’s mission is to provide EUpolicies with  independent, evidence‐based scientific and  technical  support  throughout  the wholepolicy cycle.  Working  in  close  cooperation  with  policy  Directorates‐General,  the  JRC  addresses  key  societal challenges  while  stimulating  innovation  through  developing  new  standards,  methods  and  tools, and sharing and transferring its know‐how to the Member States and international community.  Key policy areas include: environment and climate change; energy and transport; agriculture andfood security; health and consumer protection; information society and digital agenda; safety andsecurity including nuclear; all supported through a cross‐cutting and multi‐disciplinary approach. 

LF‐NA‐25392‐EN

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